• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.99-106
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• 2013

In Instant message service, the server should process instant messages and request messages which include many presence resources for users. And it also precesses massive notification messages generating from the subscribed presence resources. In this paper a new architecture of instant message service with multiple servers which can distribute loads efficiently as the number of users increases has been suggested. It also provides various functions to users using extended call processing language. The user subscribes presence information and call processing language script which describes user's functions. The server processes instant messages, presence services and call processing language scripts. New extended presence information data structure has been suggested and new call processing language operation tags have been added. Therefore extendability of the system can be increased and various services which combine presence service and call processing can be provided in this system. Furthermore instant message processing module has been integrated in the server to decrease the amount of SIP(Session Initiation Protocol) messages, and it also improves system efficiency, The performance of our proposed system has been analysed by experiments.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.905-922
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• 2021

Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is common to perform tandem analysis, K-means cluster analysis after reducing the number of variables using dimension reduction methods. However, there is no guarantee that the reduced dimension reveals the cluster structure properly. Principal component analysis may mask the structure of clusters, especially when there are large variances for variables that are not related to cluster structure. To overcome this, techniques that perform dimension reduction and cluster analysis simultaneously have been suggested. This study proposes probabilistic reduced K-means, the transition of reduced K-means (De Soete and Caroll, 1994) into a probabilistic framework. Simulation shows that the proposed method performs better than tandem clustering or clustering without any dimension reduction. When the number of the variables is larger than the number of samples in each cluster, probabilistic reduced K-means show better formation of clusters than non-probabilistic reduced K-means. In the application to a real data set, it revealed similar or better cluster structure compared to other methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.350-356
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• 2018

The contact force, which is the dynamic interaction between the pantograph and the catenary, is an important indicator for evaluating the current collecting quality, which is a stable power supply characteristic to the vehicle. In this study, dynamic contact force characteristics of pantograph of HEMU-430X vehicle, which is a power-distributed high-speed train test vehicle, were analyzed according to the catenary tension and compared with the analytical results using the pantograph-catenary interaction model. As a result of comparing the test results with the analytical results, it was confirmed that the average contact force and the standard deviation of the contact force, which are the main dynamic contact force characteristics, coincide relatively well. Using the analytical model, the relationship between the catenary tension and the contact force is presented according to the vehicle speed, and the optimal catenary tension for each operation speed is presented and compared with the international standard. As a result, it was found that the results obtained from the analysis are comparable to those recommended by international standards.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.73-82
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• 2019

In order to build a smart factory, building a CPPS (Cyber Physical Product System) is an important system that must be accompanied. Through the CPPS, it is the reality of smart factories to move physical factories to a digital-based cyber world and to intelligently and autonomously monitor and control them. But The existing CPPS architectures present only an abstract modeling architecture, and the research that applied the OPC UA Framework (Open Platform Communication Unified Architecture), an international standard for data exchange in the smart factory, as the basic system of CPPS It was insufficient. Therefore, it is possible to implement CPPS that can include both cloud and IoT by collecting field data distributed by CPPS architecture applicable to actual factories and concentrating data processing in a centralized In this study, we implemented CPPS architecture through central OPC UA Server based on OPC UA conforming to central processing OPC UA Framework, and how CPPS logical process and data processing process are automatically generated through OPC UA modeling processing We have proposed the CPPS architecture including the model factory and implemented the model factory to study its performance and usability.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.1
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• pp.17-28
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• 2019

In the financial investment management strategy, the distributed investment selecting and combining various financial assets is called portfolio management theory. In recent years, the blockchain based financial assets, such as cryptocurrencies, have been traded on several well-known exchanges, and an efficient portfolio management approach is required in order for investors to steadily raise their return on investment in cryptocurrencies. On the other hand, deep learning has shown remarkable results in various fields, and research on application of deep reinforcement learning algorithm to portfolio management has begun. In this paper, we propose an efficient financial portfolio investment management method based on Asynchronous Advantage Actor-Critic (A3C), which is a representative asynchronous reinforcement learning algorithm. In addition, since the conventional cross-entropy function can not be applied to portfolio management, we propose a proper method where the existing cross-entropy is modified to fit the portfolio investment method. Finally, we compare the proposed A3C model with the existing reinforcement learning based cryptography portfolio investment algorithm, and prove that the performance of the proposed A3C model is better than the existing one.

• Membrane Journal
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• v.29 no.1
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• pp.44-50
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• 2019

In this paper, we developed mixed matrix membranes (MMMs) consisting of SBS-g-POEM block-graft copolymer, ionic liquid (EMIMTFSI) and ZIF-8 nanoparticles to separate a $CO_2/N_2$ gas pair. The SBS-g-POEM is a rubbery block-graft copolymer synthesized through low-cost free-radical polymerization. The EMIMTFSI was dissolved into the SBS-g-POEM matrix and solution synthesized ZIF-8 nanoparticles were also dispersed into the copolymer matrix. The physico-chemical properties of manufactured membranes were characterized by Fourier transform infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), X-ray diffraction (XRD), which showed that the components were compatible with each other. The gas separation performance was confirmed by time-lag measurements showing $CO_2$ permeability of 537.0 barrer and $CO_2/N_2$ selectivity of 15.2. The result represents the EMIMTFSI and ZIF-8 nanoparticles improves the gas permeability more than two-times, without significantly sacrificing the $CO_2/N_2$ selectivity.

• Convergence Security Journal
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• v.18 no.1
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• pp.19-31
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• 2018

As the ICT technologies advance, the unprecedently large amount of digital data is created, transferred, stored, and utilized in every industry. With the data scale extension and the applying technologies advancement, the new services emerging from the use of large scale data make our living more convenient and useful. But the cybercrimes such as data forgery and/or change of data generation time are also increasing. For the data security against the cybercrimes, the technology for data integrity and the time verification are necessary. Today, public key based signature technology is the most commonly used. But a lot of costly system resources and the additional infra to manage the certificates and keys for using it make it impractical to use in the large-scale data environment. In this research, a new and far less system resources consuming signature technology for large scale data, based on the Hash Function and Merkle tree, is introduced. An improved method for processing the distributed hash trees is also suggested to mitigate the disruptions by server failures. The prototype system was implemented, and its performance was evaluated. The results show that the technology can be effectively used in a variety of areas like cloud computing, IoT, big data, fin-tech, etc., which produce a large-scale data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.648-655
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• 2019

This paper proposes the differential development of a Taekwondo electronic body protector. For this development, the most suitable sensor system was selected after analyzing and testing various sensor methods (magnetic sensors, electric capacity sensors, contact switch sensors, and piezo-film sensors) that could be applied in the electronic body protector, the selected sensors were distributed to the body and feet to make a more precise hit score, unlike the existing system in which all sensors are centralized on the body. Furthermore, it aims to illuminate using a lightweight film-type piezoelectric sensor on the body protector. In the case of an existing electronic body protector, all sensors and network device were concentrated on the body protector, so users need to purchase a set if they want it. On the other hand, the proposed system cloud can be used individually using a smart scoring WEP program. The effects of decreasing weight by up to 20% were compared with those of the existing system. Setting up a test facility is very difficult, so more study will be needed to analyze the effects of a hit.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.36-46
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• 2019

The number of hosts connected to the Internet has increased dramatically, introducing the Domain Name System(DNS) in 1984. DNS is now an important key point for all users of the Internet by allowing them to use a convenient character address without memorizing a series of numbers of complex IP address. However, relative to the importance of DNS, there still exist many problems such as the authorization allocation issue, the disputes over public registration, security vulnerability such as DNS cache poisoning, DNS spoofing, man-in-the-middle attack, DNS amplification attack, and the need for many domain names in the age of hyper-connected networks. In this paper, to effectively improve these problems of existing DNS, we proposed a method of implementing DNS using distributed ledger technology, blockchain, and implemented using a Ethereum-based platform. In addition, the qualitative analysis performance comparative evaluation of the existing domain name registration and domain name server was conducted, and conducted security assessments on the proposed system to improve security problem of existing DNS. In conclusion, it was shown that DNS services could be provided high security and high efficiently using blockchain.

• Membrane Journal
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• v.28 no.6
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• pp.379-387
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• 2018

This study was conducted to improve the membrane characteristics and performance by increasing hydrophilicity by adding additives to the ultrafiltration polysulfone (PSf) hollow fiber membrane. The mixed matrix membranes (MMMs) were prepared by dispersing 15 nm of fumed silica (FS) in the spinning solution at 0.1, 0.3 and 0.5 wt%. SEM analysis was carried out to confirm the cross-section and surface condition. It was confirmed that mean pore radius of the hollow fiber increased by 4 nm as FS was added. In addition, contact angle measurement was carried out for the hydrophilicity analysis of hollow fiber membranes, and it was confirmed that the hydrophilicity of MMMs were increased by adding of FS. In the case of water permeability, the membrane including FS showed 91~96 LMH and showed 5~11% more increase than PSf membrane. In the antifouling performance test, relative flux reduction ratios of FS mixed hollow fiber membranes were lower than that of PSf membranes, and it was confirmed that increase of hydrophilicity hinders adsorption of hydrophobic BSA on the membrane surface.